Healthcare ML Engineer — Predictive Analytics & NLP

TapestryHealth; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

TapestryHealth is seeking an experienced Machine Learning Engineer to design, build, and deploy ML solutions in a healthcare context. You will turn data into actionable insights, collaborate with product and engineering teams, and drive data-informed improvements across services and operations.

The role emphasizes end-to-end ML lifecycle, strong statistical foundations, and clear communication to stakeholders while ensuring HIPAA-compliant data handling and robust model monitoring.

Qualifications

• Master's degree in Statistics, Computer Science, or quantitative field.
• 2+ years of healthcare domain experience.
• Proven experience delivering predictive analytics in production environments.
• Proficient in Python, R, SQL or similar scripting languages.

Responsibilities

• Design, develop, and productionize ML solutions.
• Collaborate with product managers, engineers, and stakeholders as ML expert.
• Handle full ML lifecycle: problem definition, data exploration, feature engineering, training, validation, deployment.
• Participate in code reviews, testing, and QA processes.
• Ensure model reliability, monitoring, and compliance with HIPAA.

Skills

Predictive analytics

Machine learning

Natural language processing

Python automation

Data visualization

R

SQL

Python

Education

Master's degree in Statistics/CS or quantitative field

Tools

SPARK

Prefect

Airflow

MLFlow

Kedro

Git

DVC

Job description

TapestryHealth is seeking an experienced Machine Learning Engineer to design, build, and deploy ML solutions in a healthcare context. You will turn data into actionable insights, collaborate with product and engineering teams, and drive data-informed improvements across services and operations.

The role emphasizes end-to-end ML lifecycle, strong statistical foundations, and clear communication to stakeholders while ensuring HIPAA-compliant data handling and robust model monitoring.